Supplementary materials related to the paper "Evaluation of energy transition pathways for the instant coffee industry"

This document includes the configuration design codes and the data produced from the simulation of Magnetic Inductive Swing Adsorption. Furthermore, the document also consists of the surrogates produced for the optimisation study. This reduces the installation of IDAES/Pyomo/PETSc in a new conda environment.

Included in the CHEMCAD flowchart simulation model, this VBA source code extracts the inputs for the machine learning (ML) model from the simulation, passes them to the machine ML (Python), and sends the ML model outputs back to the simulation model. This code is not provided for direct use, but rather to demonstrate the methodology and as an aid for interested parties to develop their own solutions.

This document provides supplementary material supporting the Conference Paper “A Multi-Objective Optimisation and Superstructure-Based Decision-Support Tool for Regional Low-Carbon Hydrogen Roadmaps: Methodology and Application to a region of Spain”.

It includes additional methodological details, input data, model assumptions, and extended results that complement the analyses presented in the main manuscript.

Supporting Information document to submission for European Symposium of Computer Aided Process Engineering 2026

Historical US prices for oil, natural gas, and coal from 1984 to March 2026. Prices are adjusted for inflation and are expressed on a per-energy content basis. Key historical events that cause changes to price are annotated.

This talk provides background and context for the rapidly changing political shift toward support for nuclear energy in Norway. The talk explains why the Norwegian political discussion has changed, based on increased energy demand, bans or restrictions on most other forms of energy production in the country, its very low carbon footprint, and its relationship with energy policy in the EU. Also includes basic information on how nuclear power is produced and how it could be used in a Norwegian electric grid.

Aluminium cold rolling is an energy-intensive process that has a substantial impact on CO₂ emis-sions and production cost, yet plant-level optimization remains challenging due to strong process nonlinearities and various operational constraints. This study develops a physics-consistent hy-brid model that combines a Stone–Hitchcock–Ludwik analytical rolling-energy formulation with a residual deep neural network to predict the daily electricity consumption of three single-stand cold rolling mills. Using plant raw data, the hybrid model achieves lower prediction errors than conventional data driven model and yields line-specific physical parameters that agree well with the observed behaviour of each mill. On this basis, an NSGA-II-based tri-objective optimization is carried out to minimise daily energy use, CO₂ emissions, and specific production cost (SPC) by adjusting pass-wise reduction and tension schedules and line-wise production allocation. Case studies on a representative operating... [more]

The attached table shows the raw experimental data used for Figure 2 in the conference paper.

Digital supplementary information for the ESCAPE36 conference paper titled: High Performance HPs Using Tailored Refrigerants

Anomaly detection is essential for keeping chemical plants safe and running efficiently. Although many deep-learning methods have been proposed, most are still tested mainly on synthetic benchmarks such as the Tennessee Eastman Process (TEP). While these simulators enable fair comparisons, they do not reflect the noise, complexity, and irregular fault behavior of real industrial plants. As a result, it remains unclear how well these models generalize in practice. In this work, we extend our earlier ESCAPE study and move beyond water systems to industrially relevant chemical processes. We analyze data from two continuously operated pilot plant scenarios at the Technical University of Munich: n-butanol/water heteroazeotropic distillation and poly(oxymethylene) ether purification. We published these datasets for the first time at NeurIPS 2025. In this work, 30 anomaly detection methods, including 26 deep-learning and 4 classical approaches, are benchmarked using the open-source TimeSeAD l... [more]

Model simulation flowsheet of biomass gasification combined cycle system for simultaneous power and hydrogen production coupled with direct air capture in Aspen Plus.

Supplementary Material for Estimation of Thermodynamic Properties for Cellulosic Biomass-Derived Compounds: Application to Heat and Work Balances in Process Simulation that will be submitted to Escape36.

SUPPORTING INFORMATION for the work "Particle Swarm Optimization for simultaneous design and optimization of heat pumps considering Mixed Integer problems", submited to ESCAPE 36.

This document provides the Supplementary Material for the study titled: Virtual Plant–Model Pair as a Step Towards Real-Time Optimization of a Simulated Moving Bed System. The work has been submitted to the peer-reviewed proceedings of the 36th European Symposium on Computer-Aided Process Engineering (ESCAPE 2026).

This document contains digital supplementary material for the article “An Extended Superstructure Formulation for Non-Isobaric Flowsheet Synthesis”, submitted to the peer-reviewed proceedings of the 36th European Symposium on Computer-Aided Process Engineering (ESCAPE 2026).

Supplementary material for: Generative AI for the optimal design of seawater desalination processes (ESCAPE 36, Sheffield, June 2026)

This document contains digital supplementary material for the article “Integrated molecular and process design with technoeconomic and lifecycle assessment for solvent-based recycling of end-of-life vehicle plastics,” submitted to the peer-reviewed proceedings of the 36th European Symposium on Computer-Aided Process Engineering (ESCAPE 2026).

This document provides digital supplementary material related to the article “Development of a methodology for heat pump-based heat integration in batch processes” which has been submitted to the peer-reviewed proceedings of the 36th European Symposium on Computer-Aided Process Engineering (ESCAPE 2026).

Supplementary material for "Techno-Economic Assessment of Decarbonization Pathways for Methanol and Formaldehyde Production: A Superstructure Optimization Approach" (ESCAPE36, Sheffield, June 2026)

Supplementary material for the conference paper "Evaluating the potential of e-fuels for decarbonizing European truck transport: A techno-economic and life cycle approach" (ESCAPE36, Sheffield, June 2026).

Aspen Plus is used to simulate the process and compute the mass and energy flows for the complete process of polystyrene waste conversion into value-added chemicals. This demonstrates a pathway for the recycling of PS waste, which could contribute to a more sustainable industry environment

We designed a novel methylcyclohexane–toluene–hydrogen (MTH) based chemical heat pump (CHP) and determined its key performance indicators using Aspen Plus process simulations.

This document compiles the digital supplementary material associated with the article entitled “Optimizing Steam Flux for Energy Efficiency in Ammonia Recovery during Sodium Carbonate Production”, published in the peer-reviewed proceedings of the 36th European Symposium on Computer Aided Process Engineering (ESCAPE 36). It presents the effects of variations in steam pressure and temperature on the system’s temperature and mass flow rate.

The climate crisis and dependence on fossil fuels make the transition to renewable energy sources imperative, with biomass standing out for promoting decarbonization and circular economy. In this context, fluidized bed gasification emerges as an efficient route for converting waste into syngas, applicable to power and hydrogen generation. Given the variability of real operating conditions, dynamic models are essential to represent coupled fluid dynamic, thermal, and kinetic phenomena over time. In this work, a dynamic phenomenological model was developed using a lumped 0D ap-proach, in which the reactor is divided into two interacting zones represented as continuous stirred-tank reactors (CSTRs): a dense bed, where drying, devolatilization, and heterogeneous re-actions occur, and a freeboard, dominated by homogeneous gas-phase reactions. The model was validated against experimental data from a bubbling fluidized bed gasifier, showing good agree-ment for major syngas species (CO and H₂,... [more]